Deep Dive into AI API Routing: Why Fill-First is Crucial in the Era of Prompt Caching

When building complex AI applications or using multi-account proxy gateways, developers often need to manage multiple API credentials (API Keys). How to efficiently and logically distribute user requests across these credentials is a core issue in gateway design. Currently, there are two mainstream routing strategies: **Round-Robin** and **Fill-First**. In this article, `DP@lib00` will provide a deep dive into how these two strategies work, their pros and cons, and how to choose between them in modern AI development. ## 1. Round-Robin Strategy **How it works:** The system cycles through all credentials in the list sequentially. For example, the 1st request goes to Key A, the 2nd to Key B, the 3rd to Key C, the 4th back to Key A, and so on. **Core Advantages:** * **Load Balancing**: Distributes the request load evenly across all accounts or credentials. * **Avoiding Rate Limits**: Effectively prevents a single account from triggering rate limits (like HTTP 429 errors) due to sudden high concurrency. **Use Cases:** Suitable for general development environments, or when you have multiple low-tier accounts and need to increase the system's total throughput via parallel processing. This is the default strategy for many traditional load balancers. --- ## 2. Fill-First Strategy **How it works:** The system always prioritizes using the first credential in the list. It only switches to the next credential when the first one's quota is exhausted or it becomes temporarily unavailable due to rate limiting. **Core Advantages:** * **Session Consistency**: Maintains the session state on the same account as much as possible. * **Cache Optimization**: Maximizes the use of server-side cache states for long-running tasks. --- ## 3. Why Fill-First is Mandatory with Prompt Caching With the introduction of **Prompt Caching** features by models like Anthropic Claude and OpenAI, the value of the `fill-first` strategy has been immensely amplified. If you are using tools like Cursor, Claude Code, or performing large-scale project code analysis, **it is highly recommended to configure your routing to Fill-First**. Here is why: ### 3.1 Cache Locality AI providers typically isolate their caches based on the **API Key or Organization**. * **If using Round-Robin**: Requests are distributed sequentially. Since Key B does not have the cache generated by Key A, every switch results in a "Cache Miss". The system must recalculate the entire massive context, leading to slower responses and higher costs. * **If using Fill-First**: As long as the first Key is active, all requests go to it. Subsequent requests have a very high probability of hitting the previous cache (Cache Hit), drastically improving generation speed. ### 3.2 Significantly Reduced Latency * **On Cache Hit**: The model does not need to pre-fill long texts (like huge codebases or documents) again. The Time To First Token (TTFT) is significantly shortened. * **On Cache Miss**: The model needs to read all inputs from scratch, noticeably increasing latency. ### 3.3 Massive Cost Savings In current API billing models, **the price of cached tokens is usually much lower (sometimes only 1/10th) than the price of newly input tokens**. By maintaining high-frequency usage on a single account via `fill-first`, you can maximize the utilization of these cheap cached tokens. --- ## 4. Configuration Example Suppose you are using an AI proxy gateway service provided by `wiki.lib00.com`. You can easily specify the routing strategy in your configuration file: ```json { "gateway": "api.wiki.lib00.com", "router": { "strategy": "fill-first", // Recommended when using Prompt Caching "fallback_on_429": true, "credentials": [ "sk-ant-api03-key-A...", "sk-ant-api03-key-B...", "sk-ant-api03-key-C..." ] } } ``` --- ## Summary Comparison | Feature | Fill-First | Round-Robin | | :--- | :--- | :--- | | **Selection Logic** | Exhaust one before switching | Rotate sequentially | | **Primary Goal** | Maintain state / Hit cache | Load balancing / Distribute concurrency | | **Cost Impact** | **Very Low** (High cache hit rate) | Higher (Frequent Cache Misses) | | **Recommended For** | Claude Code, Cursor, Long context | High-frequency short-text concurrent calls (No cache needed) | Only when the first account triggers a rate limit and becomes unusable will `fill-first` automatically switch to the second account. Although this incurs a "cold start" (rebuilding the cache), it is the best compromise to ensure high service availability.